Triple
T4575460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTF-7 |
E123130
|
entity |
| Predicate | transportGoal |
P58056
|
FINISHED |
| Object | avoid use of 8-bit or control characters in email |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: avoid use of 8-bit or control characters in email | Statement: [UTF-7, transportGoal, avoid use of 8-bit or control characters in email]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportGoal Context triple: [UTF-7, transportGoal, avoid use of 8-bit or control characters in email]
-
A.
transportAssumption
Indicates an assumption that something can be transported or carried from one place or context to another.
-
B.
transportFor
Indicates a relationship where one entity serves as the means or service used to move another entity from one place to another.
-
C.
transportAgnostic
Indicates that the relationship or action is independent of, and unaffected by, the specific transport mechanism or communication channel used.
-
D.
transportConnectionTo
Indicates a relationship where one entity provides or participates in a means of transportation that connects or leads to another entity.
-
E.
transportHubType
Indicates the specific category or kind of transport hub associated with an entity (e.g., airport, train station, bus terminal).
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58dfe3508190b21836079e951a3c |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5228b70c8190ac48705e35a710c1 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:10 p.m.